Abstract
The field of digital and data communications is becoming increasingly dominant because digital transmission offers data processing options and flexibilities not available with analog transmission. The main feature of a digital communication system is that during a finite interval of time, it sends a waveform from a finite set of possible waveform. One of the most important and fundamental models of communications channels is the binary symmetric channel (BSC). An important measure of system performance in a digital communication system is the probability of error. In this paper, the probability of error, the reliability, the entropy and the channel capacity of a BSC model are studied under non‐Gaussian noise disturbances. Namely, Cauchy, Laplace and logistic distributions are considered. It is found that the reliability of the signaling system is low under non‐Gaussian noise distributions compared to the Gaussian noise distribution. Several methods were used to reduce the error probability. The amount of improvement in reliability using the reduction methods is higher in the case of Gaussian noise. In order to achieve high reliability under non‐Gaussian noise distribution, it is required to increase signal‐to‐noise ratio (SNR) and increase number of repetitions when sending the same signal different times. Finally, it is observed that increasing the reliability for Cauchy distribution noise has totally failed based on sending the same signal different times and summing the received signals. Copyright © 2003 John Wiley & Sons, Ltd.